{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T10:12:52Z","timestamp":1772619172671,"version":"3.50.1"},"reference-count":30,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,8]]},"DOI":"10.1109\/icpr.2018.8545381","type":"proceedings-article","created":{"date-parts":[[2018,11,30]],"date-time":"2018-11-30T00:17:38Z","timestamp":1543537058000},"page":"1121-1126","source":"Crossref","is-referenced-by-count":17,"title":["Anomaly Detection via Minimum Likelihood Generative Adversarial Networks"],"prefix":"10.1109","author":[{"given":"Chu","family":"Wang","sequence":"first","affiliation":[]},{"given":"Yan-Ming","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Cheng-Lin","family":"Liu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/469"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2014.2303895"},{"key":"ref11","first-page":"115","article-title":"A spectral-spatial based local summation anomaly detection method for hyperspectral images. Signal Processing","volume":"124","author":"du","year":"2016","journal-title":"Big Data Meets Multimedia Analytics"},{"key":"ref12","author":"eghbal-zadeh","year":"2017","journal-title":"Likelihood estimation for generative adversarial networks"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MLSP.2004.1422961"},{"key":"ref14","first-page":"2672","article-title":"Generative adversarial nets","volume":"27","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref15","author":"grover","year":"2017","journal-title":"Flow-gan Bridging implicit and prescribed learning in generative models"},{"key":"ref16","article-title":"One class support vector machines for detecting anomalous windows registry accesses","volume":"9","author":"heller","year":"2003","journal-title":"Proc of the Workshop on Data Mining for Computer Security"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"26","DOI":"10.5120\/3399-4730","article-title":"A review of anomaly based intrusion detection systems","volume":"28","author":"jyothsna","year":"2011","journal-title":"International Journal of Computer Applications"},{"key":"ref18","author":"boesen","year":"2015","journal-title":"Autoencoding beyond pixels using a learned similarity metric"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref28","first-page":"81","article-title":"A multi-agent simulation system for prediction and scheduling of aero engine overhaul","author":"stranjak","year":"2008","journal-title":"Proceedings of the 7th international Joint Conference on Autonomous Agents and Multiagent Systems industrial Track"},{"key":"ref4","first-page":"395","article-title":"A linear programming approach to novelty detection","author":"campbell","year":"2001","journal-title":"Advances in neural information processing systems"},{"key":"ref27","author":"schreyer","year":"2017","journal-title":"Detection of anomalies in large scale accounting data using deep autoencoder networks"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1080\/01431160110055804"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/WCICA.2006.1713148"},{"key":"ref5","author":"chalapathy","year":"2017","journal-title":"Robust deep and inductive anomaly detection"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/11760191_121"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ISCC.2006.1691116"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2003.08.006"},{"key":"ref9","author":"dai","year":"2017","journal-title":"Good Semi-supervised Learning that Requires a Bad GAN"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2007.53"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2011.01.019"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2017.7966273"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2007.368917"},{"key":"ref24","first-page":"2226","article-title":"Improved techniques for training gans","author":"salimans","year":"2016","journal-title":"Advances in neural information processing systems"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296547"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/089976601750264965"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1007\/978-3-319-59050-9_12","article-title":"Unsupervised anomaly detection with generative adversarial networks to guide marker discovery","author":"schlegl","year":"2017","journal-title":"International Conference on Information Processing in Medical Imaging"}],"event":{"name":"2018 24th International Conference on Pattern Recognition (ICPR)","location":"Beijing","start":{"date-parts":[[2018,8,20]]},"end":{"date-parts":[[2018,8,24]]}},"container-title":["2018 24th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8527858\/8545020\/08545381.pdf?arnumber=8545381","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T14:08:19Z","timestamp":1643292499000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8545381\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/icpr.2018.8545381","relation":{},"subject":[],"published":{"date-parts":[[2018,8]]}}}